Building an efficient Continuous Integration workflow on HPC systems

Continuous Integration (CI) is a central cornerstone of modern software development practices, but its usage in High Performance Computing (HPC) contexts brings a set of challenges that are yet to be tackled fully across different libraries and computing centers. We want to share our own path in the development of a modern HPC library, moving from a single development node to multiple nodes and onto SLURM-managed HPC systems. We will cover the following topic areas: Container image generation and deployment Rootless container execution and custom executors Interaction with SLURM through a custom executor or ephemeral runners Accounting and security model Build performance profiling and optimization Test performance and split build/test execution What do we need from computing center operators? A recording of this session is available on YouTube: https://youtu.be/xchS7wef0L0

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-06
DOI
https://doi.org/10.5281/zenodo.14290374
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

Building an efficient Continuous Integration workflow on HPC systems

Zenodo (CERN European Organization for Nuclear Research)
Parallel Computing and Optimization Techniques
article

Building an efficient Continuous Integration workflow on HPC systems

article en

Abstract

Continuous Integration (CI) is a central cornerstone of modern software development practices, but its usage in High Performance Computing (HPC) contexts brings a set of challenges that are yet to be tackled fully across different libraries and computing centers. We want to share our own path in the development of a modern HPC library, moving from a single development node to multiple nodes and onto SLURM-managed HPC systems. We will cover the following topic areas: Container image generation and deployment Rootless container execution and custom executors Interaction with SLURM through a custom executor or ephemeral runners Accounting and security model Build performance profiling and optimization Test performance and split build/test execution What do we need from computing center operators? A recording of this session is available on YouTube: https://youtu.be/xchS7wef0L0

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 54%
Parallel Computing and Optimization Techniques
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